Gain an advantage in today’s competitive job market by learning to code and to understand data science.
The University of Chicago’s eight-week Statistics for Data Science course will prepare you to solve complex challenges with data and drive important decision-making processes. You will learn to code at an introductory level and take the first steps to becoming a data scientist.
Designed for aspiring data scientists who would like to learn to code, those with computer science backgrounds, and those looking to begin a career in data science.
Statistics for Data Science is a highly practical course that will provide you with the foundational tools to solve data science problems and prepare you to take the next steps in the world of machine learning. After completing the course, you will be able to:
- Build a classification model and interpret results
- Understand the concept of hypothesis testing
- Learn the intricacies of logistic regression, evaluate its outputs, and comprehend how a link function works
- Handle a data set to produce a specified set of results
- Perform a Principal Components Analysis (PCA) to provide meaningful insights on the original data set
- Perform multiple pairwise comparisons and analyze models with multiple categorical predictors
- Present a start-to-finish analysis with meaningful insights on a data set using exploratory analysis, dimension reduction, linear models, and classification models
- Eight weeks in length
- Weekly, self-paced interactive learning modules and assignments are time-sensitive and should be completed by the set deadlines
- Synchronous sessions and live question and answer sessions
- Mentors will provide continuous support and encourage a dynamic and positive learning environment
You Will Learn To:
- Solve data science problems and prepare to take the next steps in the world of machine learning
- Understand RStudio and its application
- Gain confidence handling and manipulating data
- Interpret data and be able to communicate it effectively
Data is a commodity, and statisticians who know how to code and who understand data science are in high demand across industries. Statistics, the art of finding structure in and gleaning deeper insights from data, is among the most vital means of analyzing and quantifying uncertainty, and statistical methods are crucial to data science. The overall employment market for mathematicians and statisticians is expected to grow by 33% over the next decade.
Potential Job Titles for Data Science-Applied Statistics
- Analytics Consultant
- Data Insight Analyst
- Data Scientist
- Machine Learning Specialist